{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ed2d39e9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "数据形状: (1934, 1025)\n",
      "\n",
      "数据前5行:\n",
      "   对应数字  0  1  2  3  4  5  6  7  8  ...  1014  1015  1016  1017  1018  1019  \\\n",
      "0     0  0  0  0  0  0  0  0  0  0  ...     0     0     0     0     0     0   \n",
      "1     0  0  0  0  0  0  0  0  0  0  ...     0     0     0     0     0     0   \n",
      "2     0  0  0  0  0  0  0  0  0  0  ...     0     0     0     0     0     0   \n",
      "3     0  0  0  0  0  0  0  0  0  0  ...     0     0     0     0     0     0   \n",
      "4     0  0  0  0  0  0  0  0  0  0  ...     0     0     0     0     0     0   \n",
      "\n",
      "   1020  1021  1022  1023  \n",
      "0     0     0     0     0  \n",
      "1     0     0     0     0  \n",
      "2     0     0     0     0  \n",
      "3     0     0     0     0  \n",
      "4     0     0     0     0  \n",
      "\n",
      "[5 rows x 1025 columns]\n",
      "\n",
      "特征维度: (1934, 1024)\n",
      "目标变量类别: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n",
      "各类别样本数量:\n",
      "0    189\n",
      "1    198\n",
      "2    195\n",
      "3    199\n",
      "4    186\n",
      "5    187\n",
      "6    195\n",
      "7    201\n",
      "8    180\n",
      "9    204\n",
      "Name: count, dtype: int64\n",
      "\n",
      "训练集大小: (1547, 1024)\n",
      "测试集大小: (387, 1024)\n",
      "\n",
      "开始训练模型...\n",
      "模型训练完成!\n",
      "\n",
      "预测结果前50个:\n",
      "[8 2 1 1 9 2 8 5 5 4 2 5 1 8 6 5 1 5 8 3 4 9 8 9 1 9 4 1 7 1 7 9 9 1 8 6 8\n",
      " 8 3 0 5 4 5 7 3 0 9 9 2 1]\n",
      "\n",
      "预测值与实际值对比（前10个）:\n",
      "   预测值  实际值\n",
      "0    8    8\n",
      "1    2    2\n",
      "2    1    1\n",
      "3    1    1\n",
      "4    9    9\n",
      "5    2    2\n",
      "6    8    8\n",
      "7    5    5\n",
      "8    5    5\n",
      "9    4    4\n",
      "\n",
      "=== 模型评估结果 ===\n",
      "准确率 (accuracy_score): 0.9819\n",
      "准确率 (knn.score): 0.9819\n",
      "\n",
      "=== 详细分类报告 ===\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      1.00      1.00        38\n",
      "           1       0.91      1.00      0.95        40\n",
      "           2       1.00      1.00      1.00        39\n",
      "           3       0.98      1.00      0.99        40\n",
      "           4       1.00      1.00      1.00        37\n",
      "           5       0.95      1.00      0.97        37\n",
      "           6       1.00      0.97      0.99        39\n",
      "           7       1.00      0.97      0.99        40\n",
      "           8       1.00      0.89      0.94        36\n",
      "           9       1.00      0.98      0.99        41\n",
      "\n",
      "    accuracy                           0.98       387\n",
      "   macro avg       0.98      0.98      0.98       387\n",
      "weighted avg       0.98      0.98      0.98       387\n",
      "\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "预测错误的样本数量: 7\n",
      "前5个错误预测的样本:\n",
      "     预测值  实际值\n",
      "29     1    7\n",
      "98     3    8\n",
      "183    1    8\n",
      "275    5    8\n",
      "276    1    8\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.metrics import accuracy_score, classification_report, confusion_matrix\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "\n",
    "try:\n",
    "   \n",
    "    df = pd.read_excel(r\"D:\\贺之恒的python\\pppython\\python商业数据分析\\@Python大数据分析与机器学习商业案例实战\\第7章 K近邻算法\\源代码汇总_Pycharm\\手写字体识别.xlsx\")\n",
    "    \n",
    "   \n",
    "    \n",
    "except Exception as e:\n",
    "    print(f\"读取文件时出错: {e}\")\n",
    "    # 如果文件读取失败，创建一个示例数据集用于测试\n",
    "    print(\"创建示例数据集进行测试...\")\n",
    "    from sklearn.datasets import load_digits\n",
    "    digits = load_digits()\n",
    "    df = pd.DataFrame(digits.data)\n",
    "    df['对应数字'] = digits.target\n",
    "\n",
    "print(\"数据形状:\", df.shape)\n",
    "print(\"\\n数据前5行:\")\n",
    "print(df.head())\n",
    "\n",
    "# 2.提取特征变量和目标变量\n",
    "# 确保数据是数值类型\n",
    "X = df.drop(columns='对应数字').astype(np.float64)\n",
    "y = df['对应数字'].astype(np.int64)\n",
    "\n",
    "# 确保数据是C连续的内存布局\n",
    "X = np.ascontiguousarray(X)\n",
    "y = np.ascontiguousarray(y)\n",
    "\n",
    "print(f\"\\n特征维度: {X.shape}\")\n",
    "print(f\"目标变量类别: {sorted(np.unique(y))}\")\n",
    "print(f\"各类别样本数量:\\n{pd.Series(y).value_counts().sort_index()}\")\n",
    "\n",
    "# 3.划分训练集和测试集\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    X, y, \n",
    "    test_size=0.2, \n",
    "    random_state=42,\n",
    "    stratify=y\n",
    ")\n",
    "\n",
    "# 确保训练和测试数据也是C连续的\n",
    "X_train = np.ascontiguousarray(X_train)\n",
    "X_test = np.ascontiguousarray(X_test)\n",
    "y_train = np.ascontiguousarray(y_train)\n",
    "y_test = np.ascontiguousarray(y_test)\n",
    "\n",
    "print(f\"\\n训练集大小: {X_train.shape}\")\n",
    "print(f\"测试集大小: {X_test.shape}\")\n",
    "\n",
    "# 4.模型搭建和训练 - 使用更稳定的参数\n",
    "knn = KNeighborsClassifier(\n",
    "    n_neighbors=5,\n",
    "    weights='uniform',\n",
    "    algorithm='auto',  # 让sklearn自动选择最佳算法\n",
    "    n_jobs=-1  # 使用所有可用的CPU核心\n",
    ")\n",
    "\n",
    "print(\"\\n开始训练模型...\")\n",
    "try:\n",
    "    knn.fit(X_train, y_train)\n",
    "    print(\"模型训练完成!\")\n",
    "except Exception as e:\n",
    "    print(f\"模型训练出错: {e}\")\n",
    "    # 如果标准KNN失败，尝试使用ball_tree算法\n",
    "    print(\"尝试使用ball_tree算法...\")\n",
    "    knn = KNeighborsClassifier(\n",
    "        n_neighbors=5,\n",
    "        algorithm='ball_tree',\n",
    "        n_jobs=-1\n",
    "    )\n",
    "    knn.fit(X_train, y_train)\n",
    "    print(\"模型训练完成!\")\n",
    "\n",
    "# 5.模型预测\n",
    "try:\n",
    "    y_pred = knn.predict(X_test)\n",
    "    print(f\"\\n预测结果前50个:\")\n",
    "    print(y_pred[:50])\n",
    "except Exception as e:\n",
    "    print(f\"预测时出错: {e}\")\n",
    "    # 如果批量预测失败，尝试逐个预测\n",
    "    print(\"尝试逐个样本预测...\")\n",
    "    y_pred = []\n",
    "    for i in range(len(X_test)):\n",
    "        y_pred.append(knn.predict([X_test[i]])[0])\n",
    "    y_pred = np.array(y_pred)\n",
    "    print(f\"预测结果前50个:\")\n",
    "    print(y_pred[:50])\n",
    "\n",
    "# 6.结果对比\n",
    "results = pd.DataFrame({\n",
    "    '预测值': y_pred,\n",
    "    '实际值': y_test\n",
    "})\n",
    "\n",
    "print(\"\\n预测值与实际值对比（前10个）:\")\n",
    "print(results.head(10))\n",
    "\n",
    "# 7.模型评估\n",
    "try:\n",
    "    accuracy = accuracy_score(y_test, y_pred)\n",
    "    test_score = knn.score(X_test, y_test)\n",
    "\n",
    "    print(f\"\\n=== 模型评估结果 ===\")\n",
    "    print(f\"准确率 (accuracy_score): {accuracy:.4f}\")\n",
    "    print(f\"准确率 (knn.score): {test_score:.4f}\")\n",
    "\n",
    "    # 额外的评估指标\n",
    "    print(f\"\\n=== 详细分类报告 ===\")\n",
    "    print(classification_report(y_test, y_pred))\n",
    "\n",
    "    # 8.可视化混淆矩阵\n",
    "    plt.figure(figsize=(10, 8))\n",
    "    cm = confusion_matrix(y_test, y_pred)\n",
    "    sns.heatmap(cm, annot=True, fmt='d', cmap='Blues')\n",
    "    plt.title('混淆矩阵 - 手写数字识别')\n",
    "    plt.xlabel('预测值')\n",
    "    plt.ylabel('实际值')\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "\n",
    "except Exception as e:\n",
    "    print(f\"评估模型时出错: {e}\")\n",
    "\n",
    "# 9.找出预测错误的样本\n",
    "error_mask = y_pred != y_test\n",
    "error_indices = np.where(error_mask)[0]\n",
    "\n",
    "if len(error_indices) > 0:\n",
    "    print(f\"\\n预测错误的样本数量: {len(error_indices)}\")\n",
    "    print(\"前5个错误预测的样本:\")\n",
    "    error_samples = results.iloc[error_indices].head()\n",
    "    print(error_samples)\n",
    "else:\n",
    "    print(\"\\n所有样本都预测正确!\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4bc7f13b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "数据形状: (1934, 1025)\n",
      "数据基本信息:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1934 entries, 0 to 1933\n",
      "Columns: 1025 entries, 对应数字 to 1023\n",
      "dtypes: int64(1025)\n",
      "memory usage: 15.1 MB\n",
      "None\n",
      "\n",
      "训练集大小: (1547, 1024)\n",
      "测试集大小: (387, 1024)\n",
      "开始训练各模型...\n",
      "==================================================\n",
      "训练支持向量机(SVM)...\n",
      "支持向量机(SVM) - 测试集准确率: 0.9793\n",
      "支持向量机(SVM) - 交叉验证准确率: 0.9504 (±0.0163)\n",
      "------------------------------\n",
      "训练随机森林(RF)...\n",
      "随机森林(RF) - 测试集准确率: 0.9897\n",
      "随机森林(RF) - 交叉验证准确率: 0.9623 (±0.0089)\n",
      "------------------------------\n",
      "训练逻辑回归(LR)...\n",
      "逻辑回归(LR) - 测试集准确率: 0.9690\n",
      "逻辑回归(LR) - 交叉验证准确率: 0.9493 (±0.0225)\n",
      "------------------------------\n",
      "训练K近邻(KNN)...\n",
      "K近邻(KNN) - 测试集准确率: 0.9716\n",
      "K近邻(KNN) - 交叉验证准确率: 0.9421 (±0.0081)\n",
      "------------------------------\n",
      "\n",
      "==================================================\n",
      "模型性能比较\n",
      "==================================================\n",
      "           模型    测试集准确率    交叉验证均值   交叉验证标准差\n",
      "1    随机森林(RF)  0.989664  0.962262  0.008872\n",
      "0  支持向量机(SVM)  0.979328  0.950368  0.016280\n",
      "3    K近邻(KNN)  0.971576  0.942092  0.008085\n",
      "2    逻辑回归(LR)  0.968992  0.949343  0.022489\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x1000 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "最佳模型: 随机森林(RF)\n",
      "==================================================\n",
      "测试集准确率: 0.9897\n",
      "交叉验证准确率: 0.9623 (±0.0089)\n",
      "\n",
      "详细分类报告:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      1.00      1.00        38\n",
      "           1       0.95      1.00      0.98        40\n",
      "           2       1.00      1.00      1.00        39\n",
      "           3       0.98      1.00      0.99        40\n",
      "           4       1.00      1.00      1.00        37\n",
      "           5       1.00      0.97      0.99        37\n",
      "           6       0.97      0.97      0.97        39\n",
      "           7       1.00      1.00      1.00        40\n",
      "           8       1.00      0.94      0.97        36\n",
      "           9       1.00      1.00      1.00        41\n",
      "\n",
      "    accuracy                           0.99       387\n",
      "   macro avg       0.99      0.99      0.99       387\n",
      "weighted avg       0.99      0.99      0.99       387\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "所有模型训练和评估完成!\n",
      "可视化图表已保存为PNG文件\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split, cross_val_score\n",
    "from sklearn.metrics import accuracy_score, classification_report, confusion_matrix\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "# 设置中文字体，解决方框显示问题\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei', 'Microsoft YaHei', 'DejaVu Sans']  # 用来正常显示中文标签\n",
    "plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号\n",
    "\n",
    "# 1.读取数据\n",
    "try:\n",
    "    df = pd.read_excel(r\"D:\\贺之恒的python\\pppython\\python商业数据分析\\@Python大数据分析与机器学习商业案例实战\\第7章 K近邻算法\\源代码汇总_Pycharm\\手写字体识别.xlsx\")\n",
    "except Exception as e:\n",
    "    print(f\"读取文件时出错: {e}\")\n",
    "    # 如果文件读取失败，使用sklearn自带的手写数字数据集\n",
    "    print(\"使用sklearn自带的手写数字数据集...\")\n",
    "    from sklearn.datasets import load_digits\n",
    "    digits = load_digits()\n",
    "    df = pd.DataFrame(digits.data)\n",
    "    df['对应数字'] = digits.target\n",
    "\n",
    "print(\"数据形状:\", df.shape)\n",
    "print(\"数据基本信息:\")\n",
    "print(df.info())\n",
    "\n",
    "# 2.数据预处理\n",
    "X = df.drop(columns='对应数字').astype(np.float64)\n",
    "y = df['对应数字'].astype(np.int64)\n",
    "\n",
    "# 数据标准化（对SVM和逻辑回归很重要）\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "scaler = StandardScaler()\n",
    "X_scaled = scaler.fit_transform(X)\n",
    "\n",
    "# 3.划分训练集和测试集\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    X_scaled, y, \n",
    "    test_size=0.2, \n",
    "    random_state=42,\n",
    "    stratify=y\n",
    ")\n",
    "\n",
    "print(f\"\\n训练集大小: {X_train.shape}\")\n",
    "print(f\"测试集大小: {X_test.shape}\")\n",
    "\n",
    "# 4.定义和训练三种不同的模型\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "\n",
    "models = {\n",
    "    \"支持向量机(SVM)\": SVC(random_state=42),\n",
    "    \"随机森林(RF)\": RandomForestClassifier(n_estimators=100, random_state=42),\n",
    "    \"逻辑回归(LR)\": LogisticRegression(max_iter=1000, random_state=42),\n",
    "    \"K近邻(KNN)\": KNeighborsClassifier(n_neighbors=5)  # 作为对比\n",
    "}\n",
    "\n",
    "# 存储各模型结果\n",
    "results = {}\n",
    "\n",
    "print(\"开始训练各模型...\")\n",
    "print(\"=\" * 50)\n",
    "\n",
    "for name, model in models.items():\n",
    "    print(f\"训练{name}...\")\n",
    "    \n",
    "    # 训练模型\n",
    "    model.fit(X_train, y_train)\n",
    "    \n",
    "    # 预测\n",
    "    y_pred = model.predict(X_test)\n",
    "    \n",
    "    # 计算准确率\n",
    "    accuracy = accuracy_score(y_test, y_pred)\n",
    "    \n",
    "    # 交叉验证\n",
    "    cv_scores = cross_val_score(model, X_scaled, y, cv=5, scoring='accuracy')\n",
    "    \n",
    "    # 存储结果\n",
    "    results[name] = {\n",
    "        'model': model,\n",
    "        'y_pred': y_pred,\n",
    "        'accuracy': accuracy,\n",
    "        'cv_mean': cv_scores.mean(),\n",
    "        'cv_std': cv_scores.std()\n",
    "    }\n",
    "    \n",
    "    print(f\"{name} - 测试集准确率: {accuracy:.4f}\")\n",
    "    print(f\"{name} - 交叉验证准确率: {cv_scores.mean():.4f} (±{cv_scores.std():.4f})\")\n",
    "    print(\"-\" * 30)\n",
    "\n",
    "# 5.模型比较和可视化\n",
    "print(\"\\n\" + \"=\" * 50)\n",
    "print(\"模型性能比较\")\n",
    "print(\"=\" * 50)\n",
    "\n",
    "# 创建比较表格\n",
    "comparison_df = pd.DataFrame({\n",
    "    '模型': list(results.keys()),\n",
    "    '测试集准确率': [results[name]['accuracy'] for name in results.keys()],\n",
    "    '交叉验证均值': [results[name]['cv_mean'] for name in results.keys()],\n",
    "    '交叉验证标准差': [results[name]['cv_std'] for name in results.keys()]\n",
    "}).sort_values('测试集准确率', ascending=False)\n",
    "\n",
    "print(comparison_df)\n",
    "\n",
    "# 可视化模型比较 - 修复字体问题\n",
    "plt.figure(figsize=(15, 10))\n",
    "\n",
    "# 准确率比较图\n",
    "plt.subplot(2, 2, 1)\n",
    "models_names = list(results.keys())\n",
    "test_accuracies = [results[name]['accuracy'] for name in models_names]\n",
    "cv_accuracies = [results[name]['cv_mean'] for name in models_names]\n",
    "\n",
    "x = np.arange(len(models_names))\n",
    "width = 0.35\n",
    "\n",
    "bars1 = plt.bar(x - width/2, test_accuracies, width, label='测试集准确率', alpha=0.8, color='skyblue')\n",
    "bars2 = plt.bar(x + width/2, cv_accuracies, width, label='交叉验证准确率', alpha=0.8, color='lightcoral')\n",
    "\n",
    "plt.xlabel('模型', fontsize=12)\n",
    "plt.ylabel('准确率', fontsize=12)\n",
    "plt.title('模型性能比较', fontsize=14, fontweight='bold')\n",
    "plt.xticks(x, models_names, rotation=45, fontsize=10)\n",
    "plt.legend(fontsize=10)\n",
    "plt.grid(True, alpha=0.3)\n",
    "\n",
    "# 在柱状图上添加数值标签\n",
    "def add_value_labels(bars):\n",
    "    for bar in bars:\n",
    "        height = bar.get_height()\n",
    "        plt.text(bar.get_x() + bar.get_width()/2., height,\n",
    "                f'{height:.3f}',\n",
    "                ha='center', va='bottom', fontsize=9)\n",
    "\n",
    "add_value_labels(bars1)\n",
    "add_value_labels(bars2)\n",
    "\n",
    "# 混淆矩阵可视化\n",
    "best_model_name = comparison_df.iloc[0]['模型']\n",
    "best_model = results[best_model_name]['model']\n",
    "y_pred_best = results[best_model_name]['y_pred']\n",
    "\n",
    "plt.subplot(2, 2, 2)\n",
    "cm = confusion_matrix(y_test, y_pred_best)\n",
    "sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', \n",
    "            xticklabels=range(10), yticklabels=range(10),\n",
    "            annot_kws={\"size\": 8})  # 调整注释字体大小\n",
    "plt.title(f'{best_model_name} - 混淆矩阵\\n(最佳模型)', fontsize=12, fontweight='bold')\n",
    "plt.xlabel('预测值', fontsize=10)\n",
    "plt.ylabel('实际值', fontsize=10)\n",
    "\n",
    "# 错误分析\n",
    "plt.subplot(2, 2, 3)\n",
    "error_rates = []\n",
    "for name in models_names:\n",
    "    error_rate = 1 - results[name]['accuracy']\n",
    "    error_rates.append(error_rate)\n",
    "\n",
    "bars3 = plt.bar(models_names, error_rates, color='red', alpha=0.7)\n",
    "plt.xlabel('模型', fontsize=12)\n",
    "plt.ylabel('错误率', fontsize=12)\n",
    "plt.title('各模型错误率比较', fontsize=14, fontweight='bold')\n",
    "plt.xticks(rotation=45, fontsize=10)\n",
    "plt.grid(True, alpha=0.3)\n",
    "\n",
    "# 在错误率柱状图上添加数值标签\n",
    "for bar in bars3:\n",
    "    height = bar.get_height()\n",
    "    plt.text(bar.get_x() + bar.get_width()/2., height,\n",
    "            f'{height:.3f}',\n",
    "            ha='center', va='bottom', fontsize=9)\n",
    "\n",
    "# 特征重要性（仅对随机森林）\n",
    "plt.subplot(2, 2, 4)\n",
    "if hasattr(models[\"随机森林(RF)\"], 'feature_importances_'):\n",
    "    feature_importances = models[\"随机森林(RF)\"].feature_importances_\n",
    "    # 取前15个最重要的特征（减少数量以便显示）\n",
    "    indices = np.argsort(feature_importances)[-15:]\n",
    "    \n",
    "    plt.barh(range(len(indices)), feature_importances[indices], color='green', alpha=0.7)\n",
    "    plt.yticks(range(len(indices)), [f'Feature {i}' for i in indices], fontsize=8)\n",
    "    plt.xlabel('特征重要性', fontsize=10)\n",
    "    plt.title('随机森林 - 前15个重要特征', fontsize=12, fontweight='bold')\n",
    "else:\n",
    "    # 如果没有特征重要性，显示学习曲线或其他信息\n",
    "    plt.text(0.5, 0.5, '无特征重要性数据\\n(非树模型)', \n",
    "             ha='center', va='center', transform=plt.gca().transAxes, fontsize=12)\n",
    "    plt.title('特征重要性', fontsize=12, fontweight='bold')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('模型比较结果.png', dpi=300, bbox_inches='tight')  # 保存图片\n",
    "plt.show()\n",
    "\n",
    "# 6.详细分析最佳模型\n",
    "print(f\"\\n最佳模型: {best_model_name}\")\n",
    "print(\"=\" * 50)\n",
    "\n",
    "print(f\"测试集准确率: {results[best_model_name]['accuracy']:.4f}\")\n",
    "print(f\"交叉验证准确率: {results[best_model_name]['cv_mean']:.4f} (±{results[best_model_name]['cv_std']:.4f})\")\n",
    "\n",
    "print(\"\\n详细分类报告:\")\n",
    "print(classification_report(y_test, y_pred_best))\n",
    "\n",
    "# 7.创建单独的学习曲线图\n",
    "plt.figure(figsize=(10, 6))\n",
    "training_sizes = np.linspace(0.1, 1.0, 10)\n",
    "colors = ['red', 'blue', 'green', 'orange']\n",
    "\n",
    "from sklearn.model_selection import learning_curve\n",
    "\n",
    "for i, (name, model) in enumerate(models.items()):\n",
    "    train_sizes, train_scores, test_scores = learning_curve(\n",
    "        model, X_scaled, y, cv=5, train_sizes=training_sizes,\n",
    "        scoring='accuracy', random_state=42\n",
    "    )\n",
    "    \n",
    "    train_scores_mean = np.mean(train_scores, axis=1)\n",
    "    test_scores_mean = np.mean(test_scores, axis=1)\n",
    "    \n",
    "    plt.plot(train_sizes, train_scores_mean, 'o-', color=colors[i], \n",
    "             label=f'{name} - 训练集', alpha=0.8)\n",
    "    plt.plot(train_sizes, test_scores_mean, 's--', color=colors[i], \n",
    "             label=f'{name} - 验证集', alpha=0.8)\n",
    "\n",
    "plt.xlabel('训练样本数量', fontsize=12)\n",
    "plt.ylabel('准确率', fontsize=12)\n",
    "plt.title('学习曲线比较', fontsize=14, fontweight='bold')\n",
    "plt.legend(loc='best', fontsize=10)\n",
    "plt.grid(True, alpha=0.3)\n",
    "plt.tight_layout()\n",
    "plt.savefig('学习曲线.png', dpi=300, bbox_inches='tight')\n",
    "plt.show()\n",
    "\n",
    "# 8.预测概率可视化（对于支持向量机和逻辑回归）\n",
    "plt.figure(figsize=(12, 8))\n",
    "\n",
    "for i, (name, model) in enumerate(models.items()):\n",
    "    if hasattr(model, 'predict_proba'):\n",
    "        plt.subplot(2, 2, i+1)\n",
    "        # 获取第一个测试样本的预测概率\n",
    "        probs = model.predict_proba(X_test[:1])[0]\n",
    "        plt.bar(range(len(probs)), probs, color='purple', alpha=0.7)\n",
    "        plt.xlabel('数字类别', fontsize=10)\n",
    "        plt.ylabel('预测概率', fontsize=10)\n",
    "        plt.title(f'{name} - 预测概率分布', fontsize=12)\n",
    "        plt.xticks(range(10))\n",
    "        plt.grid(True, alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('预测概率分布.png', dpi=300, bbox_inches='tight')\n",
    "plt.show()\n",
    "\n",
    "print(\"\\n所有模型训练和评估完成!\")\n",
    "print(\"可视化图表已保存为PNG文件\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bc7e2198",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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